Imported from jeremylongshore/tons-of-skills-marketplace (skills/.curated/assemblyai-core-workflow-a/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill assemblyai-core-workflow-a. Copyright stays with the author (MIT).

AssemblyAI Core Workflow A — Async Transcription

Overview

Primary money-path workflow: submit audio for async transcription with audio intelligence features. The SDK handles file upload (for local files), queues the transcription job, and polls until completion.

Prerequisites

• assemblyai package installed
• API key configured in ASSEMBLYAI_API_KEY

Instructions

Step 1: Basic Async Transcription

import { AssemblyAI } from 'assemblyai';

const client = new AssemblyAI({
  apiKey: process.env.ASSEMBLYAI_API_KEY!,
});

// Remote URL — SDK queues and polls automatically
const transcript = await client.transcripts.transcribe({
  audio: 'https://example.com/meeting-recording.mp3',
});

console.log(transcript.text);
console.log(`Duration: ${transcript.audio_duration}s`);
console.log(`Words: ${transcript.words?.length}`);

Step 2: Local File Upload

// The SDK uploads the file and transcribes in one call
const transcript = await client.transcripts.transcribe({
  audio: './recordings/interview.wav',
});

// Or from a buffer/stream
import fs from 'fs';
const buffer = fs.readFileSync('./recordings/interview.wav');
const transcript2 = await client.transcripts.transcribe({
  audio: buffer,
});

Step 3: Speaker Diarization

const transcript = await client.transcripts.transcribe({
  audio: audioUrl,
  speaker_labels: true,
  speakers_expected: 3,  // Optional: hint for expected speaker count
});

// Utterances are grouped by speaker
for (const utterance of transcript.utterances ?? []) {
  console.log(`Speaker ${utterance.speaker}: ${utterance.text}`);
  // Speaker A: Good morning, thanks for joining.
  // Speaker B: Happy to be here.
}

Step 4: Full Audio Intelligence Stack

const transcript = await client.transcripts.transcribe({
  audio: audioUrl,

  // Speaker identification
  speaker_labels: true,

  // Content analysis
  sentiment_analysis: true,
  entity_detection: true,
  auto_highlights: true,
  iab_categories: true,       // Topic detection (IAB taxonomy)
  content_safety: true,        // Flag sensitive content
  summarization: true,
  summary_model: 'informative',
  summary_type: 'bullets',

  // Formatting
  punctuate: true,
  format_text: true,
  language_code: 'en',

  // Word boost for domain terms
  word_boost: ['AssemblyAI', 'LeMUR', 'transcription'],
  boost_param: 'high',
});

// --- Access results ---

// Sentiment per sentence
for (const s of transcript.sentiment_analysis_results ?? []) {
  console.log(`[${s.sentiment}] ${s.text}`);
  // [POSITIVE] I really enjoyed working on this project.
}

// Named entities
for (const e of transcript.entities ?? []) {
  console.log(`${e.entity_type}: ${e.text}`);
  // person_name: John Smith
  // location: San Francisco
}

// Auto-highlighted key phrases
for (const h of transcript.auto_highlights_result?.results ?? []) {
  console.log(`"${h.text}" (count: ${h.count}, rank: ${h.rank})`);
}

// IAB content categories
const categories = transcript.iab_categories_result?.summary ?? {};
for (const [category, relevance] of Object.entries(categories)) {
  if ((relevance as number) > 0.5) {
    console.log(`Topic: ${category} (${((relevance as number) * 100).toFixed(0)}%)`);
  }
}

// Content safety labels
for (const result of transcript.content_safety_labels?.results ?? []) {
  for (const label of result.labels) {
    console.log(`Safety: ${label.label} (${(label.confidence * 100).toFixed(0)}%)`);
  }
}

// Summary
console.log('Summary:', transcript.summary);

Step 5: PII Redaction

const transcript = await client.transcripts.transcribe({
  audio: audioUrl,
  redact_pii: true,
  redact_pii_policies: [
    'email_address',
    'phone_number',
    'person_name',
    'credit_card_number',
    'social_security_number',
    'date_of_birth',
  ],
  redact_pii_sub: 'hash',  // Replace PII with hash. Options: 'hash' | 'entity_name'
  redact_pii_audio: true,  // Also generate redacted audio file
});

// Text has PII replaced: "My name is ####" or "My name is [PERSON_NAME]"
console.log(transcript.text);

// Get redacted audio URL (takes extra processing time)
if (transcript.redact_pii_audio_quality) {
  const redactedAudio = await client.transcripts.redactedAudio(transcript.id);
  console.log('Redacted audio URL:', redactedAudio.redacted_audio_url);
}

Step 6: Manage Transcripts

// List recent transcripts
const page = await client.transcripts.list({ limit: 20 });
for (const t of page.transcripts) {
  console.log(`${t.id} | ${t.status} | ${t.audio_duration}s`);
}

// Get a specific transcript
const existing = await client.transcripts.get('transcript-id');

// Delete a transcript (GDPR compliance)
await client.transcripts.delete('transcript-id');

Supported Audio Formats

MP3, WAV, FLAC, M4A, OGG, WebM, MP4, AAC. Max file size: 5 GB. Max duration: 10 hours (async). The SDK auto-detects format.

Output

• Complete transcript with word-level timestamps and confidence scores
• Speaker-labeled utterances (with speaker_labels: true)
• Sentiment analysis, entity detection, key phrases, topic categories
• PII-redacted text and audio
• Content safety labels for moderation

Examples

For a consented meeting recording, submit a server-controlled audio object with only the features approved for that data class, store the returned transcript ID in the operation ledger, and route transcript text and intelligence output only to the authorized downstream processor. Before deletion, reconcile the ID against the retention manifest and use a reviewed bounded batch.

Error Handling

Resources

• Transcription API Reference
• Audio Intelligence Models
• PII Redaction Guide
• Speaker Diarization

Next Steps

For real-time streaming transcription, see assemblyai-core-workflow-b. For LLM-powered analysis of transcripts, see assemblyai-sdk-patterns (LeMUR examples).